We aim to address the bottlenecks that currently exist in single-cell genomics for the study and treatment of cancer. Cancer is a highly prevalent disease that affects 1.5 million new people and claims half a million lives every year in the US alone. One promising approach to treat cancer is to personalize the treatment to the genetic background of the tumor to tailor an optimal therapy. However, the analysis of a cancer is complicated by the genetic heterogeneity of tumors. We thus need detailed information of the cell sub- populations in order to design a therapy that will treat all the cancerous cells of a tumor. This heterogeneity involves performing genomic profiling of the tumor at single-cell resolution as compared to traditional analysis averaged over the tumor. However, despite its clinical utility single-cell genomics cannot be widely adopted because of its prohibitive cost. Wit DNA sequencing costs rapidly dropping, the preparation and manipulation of cells prior to sequencing is the determining factor for the expense of single-cell genomics. Our overarching aim is to develop a technology platform that will facilitate affordable single-cell copy number variation (CNV) and biomarker profiling to support evidence-based medicine in the treatment of cancer. Implementation of our method, upon full development, will allow the physician to characterize the advancement and the spread of clones in malignant and benign-appearing regions of a tumor using biopsy cores. Physicians will have the ability to use information gleaned from single cell analyses to make decisions on the best possible treatment. Both the probability of finding aggressive clone(s) and confidence levels about the absence of such a clone directly depend on the number of cells that are analyzed. The prohibitive cost of analyzing 100 cells with current single-cell genomics methodologies prevents the wide adoption of these techniques both in research and clinical settings. We combine microfluidic technologies (droplet microfluidics, on-valve chips) and state-of-the art molecular biology techniques (barcoding, next-generation sequencing) into a robust yet simple platform that will enable the biomarker and CNV profiling of an intermediate number of single-cells (100's-1,000's). Our platform design allows for substantial cost savings with current sequencer capacities, and has built-in adaptability to new molecular protocols as well as built-in scalability of cell capacity and cost- reduction. These key provisions support the relevance of the proposed platform. We will validate and prove the clinical utility of our microfluidic platform by performing single-cell genomic profiling of tumors from patients with colon, lung, and kidney or breast cancer. Results from the described project will directly impact the development of comprehensive diagnostics and consequently personalized therapies for cancer. The successful implementation of this platform will ultimately reduce the human and economic burden of cancer therapies by enabling personalized treatments.